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The Review of Regional Studies (2017) 47, 121135 The Review of Regional Studies The Official Journal of the Southern Regional Science Association Fellows Address‒Memphis, Tennessee, March 31st, 2017 56th Meetings of the Southern Regional Science Association Searching for Isard’s Regional Essence* Doug Woodward Darla Moore School of Business, University of South Carolina, USA Abstract: At the inception of the Southern Regional Science Association in the early 1960s, Walter Isard maintained that areal regions are fundamental units of observation and analysis. To this day, understanding the special significance of regions motivates much of our empirical research. In my address, I argue that regional fixed effects estimates from regression analysis can help us comprehend the distinctive character of areal units. This paper offers two examples from my research. First, I present the results of a regression model that explains regional knowledge spillovers in U.S. counties. Santa Clara County (Silicon Valley) has by far the largest fixed effect estimate of any U.S. county. Overall, the county level fixed effects for knowledge spillovers follow a pattern of rapid exponential decay. Next, I inspect neighborhood fixed effects taken from a hedonic housing price model of the Charleston, South Carolina region. The results suggest a clear preference for coastal proximity as reflected in house prices. For neighborhoods away from the coast, the fixed effects estimates exhibit a steep decline toward zero. Like Silicon Valley’s regional advantage in knowledge, beachfront neighborhoods benefit from an exclusive, time invariant advantage that is hard, if not impossible, to replicate in space. Keywords: regional fixed effects, high-technology development, housing JEL Codes: R10, R23, R30 1. INTRODUCTION The Southern Regional Science Association (SRSA) owes its existence in large part to Walter Isard’s revelation that the region represents a distinct and elemental unit of analysis. The founding father of regional science wrote, “The region has its own ‘essence’ which can be grasped in full only by tools, hypotheses, models, and data processing techniques specifically designed for regional analysis” (Isard, 1956). In 1962, Isard helped establish our association, originally called the Southern Section of the Regional Science Association. As an academic evangelist for the new discipline, he brought his vision to Chapel Hill and presented one of four seminal papers at the “Exploratory Organization Meeting” (Durden and Knox, 2000). To this day, his conviction that the “region has its own essence” encapsulates the mission of the SRSA. The website of the North American Regional Science Council prominently displays Isard’s statement of purpose. To be sure, “essence” has a metaphysical ring to it. Certainly, Isard is not imploring us to use scientific tools to search for some mystical spirit that lies beyond the appearances of the real world. Instead, I consider Isard’s essence to mean that the region is fundamental and necessary, and importantly, something that we can detect and measure through empirical research. Woodward is Director of the Division of Research and Professor of Economics at the Darla Moore School of Business, University of South Carolina, Columbia, SC. E-mail: [email protected] © Southern Regional Science Association 2017. ISSN 1553-0892, 0048-749X (online) www.srsa.org/rrs 122 The Review of Regional Studies 47(2) In my SRSA Fellows Address, I will review how the empirical tools we have developed since the inception of our association enable us to discern the essence of regions. Through ongoing research, the fundamentals of regions can “be grasped in full,” as Isard suggested. The unifying theme of regional science, which covers migration, industry location, housing, and other real- world subjects, is that we analyze data assembled in bounded (or areal) units to study. Specifically, I contend that spatial units like counties and neighborhoods have quantifiable identities. In regional statistical analysis, we often introduce regional fixed effects. These fixed effects capture the regional heterogeneity that is otherwise “unobserved.” In regression analysis, fixed effects hold constant the unique character of regions and thus serve as controls that help isolate and accurately estimate particular influences—for example, the role of regional incentives on industrial location choices. Yet, published research papers do not usually report the fixed effect estimates. By not examining these results for fixed effects, we may overlook important information that can help us determine what is essential about regions. In this paper, I will draw on my recent research to demonstrate how the estimates for fixed effects help us quantify the special identity of regions. I also make a larger point about our own identity as an association, as reflected in Isard’s mission statement. Our objective is to develop “tools, hypotheses, models, and data processing techniques specifically designed for regional analysis.” Advancing statistical and data analytic techniques are fundamental concerns of everyone who labors in the vineyard of regional analysis. In an age where it has become alarmingly acceptable to dismiss the scientific method in favor of “fake news” and “alternative facts,” our association’s empirical research provides a valuable service. In the first section of the paper, I set the stage for my Fellows Address by discussing how I came to appreciate regional science for its enduring commitment to empirical research. To use Andy Isserman’s (2010) apt phrase, all of us in this association are voyagers on an academic “space odyssey.” I began mine when I presented my first paper at the annual meeting of the SRSA in 1985. At the time, I was a graduate student who had the privilege of working with regional forecasting pioneer Norm Glickman and Niles Hansen, one our first SRSA Fellows. Like many young scholars who are attracted to our association, I sought to acquire empirical skills and apply them to understanding pressing economic development problems. Next, I review the fundamental basis of our empirical research: the region. Mostly, we analyze data in areal units and thus we are not engaged in pure spatial analysis. Following this section, I discuss how fixed effect regression can be used to assess the essence of these regional (areal) units. I argue that this statistical technique helps us “grasp the whole” that Isard inspired us to investigate. The paper presents two examples of fixed effects as measures of regional essence: (1) U.S. county-level knowledge spillovers and the unique identity of Silicon Valley; and (2) neighborhoods fixed effects and preference for coastal real estate in the Charleston, South Carolina region. In both cases, we will see that fixed effects exhibit exponential decay. The results reveal that regions like Silicon Valley or neighborhoods like the Beachside of Charleston have a distinct essence that is hard to reproduce elsewhere. 2. EMPIRICAL EPIPHANY With one notable exception, universities and colleges do not offer regional science degree programs. SRSA past-president Michael Lahr is a rare case in that he received B.A., M.A., and © Southern Regional Science Association 2017. WOODWARD: SEARCHING FOR ISARD’S REGIONAL ESSENCE 123 Ph.D. degrees in regional science at the University of Pennsylvania. Walter Isard set up the department at Penn in the 1950s, but the university closed the program in 1993. With those options no longer available, students get exposure to regional science through economics, geography, or other subject areas. For me, discovering regional science came as an epiphany after disillusionment with the lack of concern in economics for empirical analysis while I was in graduate school. I first intended to study macroeconomics. Yet the field pivoted away from empirical research in the late 1970s and early 1990s. Macroeconomics became theoretically dogmatic, largely unscientific, and increasingly divorced from reality. At its best, macroeconomics blends theory, empirical research, and policy. The field blossomed in the 1950s and 1960s, with an emphasis on statistical research, including the development of practical macroeconomic forecast models. With an early interest in forecasting, I was motivated to study how financial instability influenced the macroeconomic business cycle. In graduate school, however, I was shocked to learn that the financial sector’s crucial, systemic role was dismissed by the theoretical orthodoxy. Moreover, I was interested in learning how policy can be used to mitigate the damage caused by recurring recessions and depressions. Yet in the mid- to late-1970s, macroeconomics moved away from its policy-driven Keynesian origins to “policy neutral” New Classical models. These models were built on unrealistic rational expectations and perfect foresight assumptions. After some mathematical gymnastics, these models attempt to show that omniscient agents anticipate and neutralize macroeconomic policy interventions. From this perspective, the notion that macroeconomic policy can affect the trajectory of the business cycles was considered a Keynesian conceit that was attacked by prominent critics, notably at the University of Chicago. Yet during the late-1970s, the conceits of New Classical macroeconomics became the conventional economic wisdom as it spread across college campuses. I witnessed this retreat from empirical inquiry to mathematical abstraction in graduate school. Nevertheless, the models were respected for
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